Abstract

In this paper, a long-term Distribution System Planning Model (DSPM) considering network reconfiguration and Distributed Generation (DG) integration, is presented. The DSPM objective functions are power loss reduction and voltage stability enhancement. The proposed model handles long-term load increase and seeks to define when and where the reinforcements, such as network reconfiguration (NR) and DG integration, are required to meet the load increase. A Binary Particle Swarm Optimization algorithm (BPSO) is used for network reconfiguration while optimal DG allocation and sizing are performed using the Voltage Stability Margin Index (VSMI) and curve fitting approximation. The planning horizon of each solution is determined through load forecasting using a Nonlinear Autoregressive neuronal network with exogenous variables (NARX) technique. The performance of the proposed model is evaluated considering several case studies on the IEEE 33-bus test system. Results demonstrate the effectiveness of the proposed approach.

摘要

在本文中，提出了考虑网络重构和分布式发电 (DG) 集成的长期配电系统规划模型 (DSPM)。DSPM 的目标函数是降低功率损耗和增强电压稳定性。所提出的模型处理长期负载增加，并试图定义何时何地需要加强网络重新配置 (NR) 和 DG 集成来满足负载增加。二元粒子群优化算法 (BPSO) 用于网络重新配置，同时使用电压稳定裕度指数 (VSMI) 和曲线拟合近似来执行最佳 DG 分配和大小调整。每个解决方案的规划范围是通过使用具有外生变量的非线性自回归神经元网络 (NARX) 技术的负载预测来确定的。考虑到 IEEE 33 总线测试系统的几个案例研究，对所提出模型的性能进行了评估。结果证明了所提出方法的有效性。